National Workshop on Advanced Deep Learning

20 May
  • @MBCET

Deep Learning percolates into the various facets of technology. The technology enables computers to capture concept level features hidden in the input data. The methods based on deep learning have a significant impact in the performance of algorithms used for speech recognition, image and video processing, text analysis and medical image processing. This workshop aims towards promoting research, assist to educators and designers in the field of deep learning. The workshop sessions and hands-on will enable participants to understand the basics of deep learning and the various deep learning architectures. The sessions will be handled by eminent members from Bennett University.


  1. Hands On with Python
  2. Basics of Convolutional Neural Networks
  3. Deep Learning Techniques for Medical Image Processing
  4. Introduction to Recurrent Neural Networks
  5. Hands On with Tensorflow 2.0
  6. Hands On with PyTorch
  7. Unsupervised Deep Learning
  8. Deep Generative Models: Autoencoders, Variational Autoencoders, GANs
  9. Advanced Deep Learning Topics in CNN
  10. Advanced Deep Learning Topics in RNN
  11. Deep Learning Model Optimization
  12. Neural Architecture Search (NAS): AutoML, Auto Keras, Multi-objective Approaches


This workshop is open to the faculty members from AICTE/UGC approved academic institutions, Research Scholars, IT Professionals and PG students.


The registration fee for participants including GST has been given below

Industry: 4000

Faculty: 3500

Research Scholar and PG students : 3000

Session Coverage – click here

Workshop Brochure – click here

Registration link – click here

Event Timing: May 20th – 22nd, 2019
Organized by: Department of Computer Science and Engineering
Venue: Mar Baselios College of Engineering and Technology, Thiruvananthapuram, Kerala

Ms. Jesna Mohan Assistant Professor

Department of CSE

MBCET  Phone: 9497467715

Mr. Ramjith R P

Assistant Professor

Department of CSE

MBCET  Phone: 9746314160

Email: [email protected]